Infrared weak and small target background inhibiting method and device on basis of global filtering

Abstract

The invention provides an infrared weak and small target background inhibiting method on the basis of global filtering. The infrared weak and small target background inhibiting method comprises the following steps: repeatedly carrying out smoothing processing on an infrared image; cascading a plurality of images in different smooth scales, which are obtained after smoothing processing, to generate an infrared image data cube; according to a local normalized Euclidian distance, separating weak and small targets and a background image in the generated infrared image data cube; according to a nonlinear function, reinforcing the weak and small targets separated according to the local normalized Euclidian distance, inhibiting the background image separated according to the local normalized Euclidian distance and obtaining an image of which the background is inhibited. The invention also provides an infrared weak and small target background inhibiting device on the basis of the global filtering. By the infrared weak and small target background inhibiting method on the basis of the global filtering method and the infrared weak and small target background inhibiting method on the basis of the global filtering device on the basis of the global filtering, shape and grey information of the targets can be better kept, the excellent preprocessed image is provided for a subsequent background inhibiting method, difference between each pixel and the background in the image can be more accurately measured, and an excellent background inhibiting effect is obtained.

Description

technical field [0001] The invention belongs to the field of infrared image processing, and in particular relates to a method and a device for suppressing the background of small infrared targets based on global filtering. Background technique [0002] In infrared early warning and search and track systems, due to the distance between the target and the detector and atmospheric attenuation, the infrared image obtained on the detector often has low contrast, blurred image details, few pixels in the image, and low signal-to-noise ratio. Low-level characteristics, which brings difficulties to the automatic detection of weak and small targets. Therefore, in order to improve the detection probability, the original infrared image must be preprocessed before detection to suppress background clutter and enhance the target. Background suppression is a key part of preprocessing, and its purpose is to suppress the undulating background in the image and improve the signal-to-noise rati...

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Problems solved by technology

For example: the method based on the bottom stagnation point filter of the time domain contour suppresses the background clutter in the time domain and detects the moving infrared weak target. The value / average filter is applied to the method of weak and small target detection, and the image is processed in the air domain, which increases the amount of calculation, and when the window is too large, it will lead to poor suppression of background clutter, and it is easy to be in the target point cycle. False contours are generated, and the positioning accuracy is poor; the weak target detection method based on morphological top-hat transformation, the suppression effect of this method on background clutter is closely related to the selection of structural elements, and the background smaller than structural elements The clutter cannot be suppressed well; using the adaptive linear prediction method of the two-dimensional least mean square error filter (TDLMS), the least mean square error criterion is used in the prediction process. When the original infrared image contains strongly correlated noise, Using the correlation of clutter, the clutter component can be predicted from the input signal of the filter and eliminated, and the target signal component can be obtained in the residual error of the filter. This method may lead to a negative signal-to-noise ratio for the non-stationary background. reduction of

[0004] In addition to the above background suppression methods, there are various background suppression methods for infrared weak and small target images, but they all have their own limitations. Especially when the image contains a complex background with high gray levels and sharp fluctuations, many methods Can't get a good suppression effect

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